Sometimes that money is returned, as Joe said, in the finances. At other times it’s invested in other things. So it might be we learn how to do things more efficiently and run systems and services more efficiently that then allow us to do things like Data Residency in a global sense. Other times in things like Atlassian Intelligence, a lot of the AI features, it’s about getting the features out first and then working out how to cost optimize over time as we watch customer usage patterns, we can work out how to scale and make that more efficient. So certainly something in engineering we spend a lot of time working on and we’ve had great results over the last two to three years. As our cloud platform has grown increasingly more complex, but also that gives us more leverage.
Operator: Your next question comes from Brent Thill from Jefferies. Please go ahead, Brent.
Brent Thill: Thanks. On Atlassian Intelligence, I believe it’s GA now, I’m curious if you could give us a sense of what we’re seeing, what you’re seeing, and then ultimately the monetization path in AI. And I guess one of the questions we’re getting is if you’re seeing a faster move to DC versus cloud, does this slow your AI adoption pathway down or not?
Scott Farquhar: Brent, I’m glad I can take that one. I was worried about you all not asking an AI question until well into the call. Just checking you’re all okay there. Look, high level, Atlassian Intelligence and AI generally is a huge advantage for Atlassian. Like, we deeply, deeply believe that. It’s a company that focuses on knowledge workers and unleashing the potential of every team. It’s a company that has a huge amount of data that customers have entrusted us with. The ability to remix, summarize, and give that data back in different forms to customers using a lot of these large language models and machine learning technologies is incredible. It’s very exciting in terms of what we can deliver. As you mentioned, the initial Atlassian Intelligence feature set largely went GA during the quarter.
It has had fantastic customer reception. There’s no other way to say that. We saw that when we announced it at Team 23 last year in Las Vegas, and we’ve continued to see that as we’ve worked with all of the early access program and then beta customers and now being in GA. The ability to change how people do work in non-technical teams and in technical teams is just an unlock. Where we talk about our mission to unleash potential of every payment. It’s literally doing that in fantastical ways. We had more than 20,000 customers that used the features during the beta period, which for us, as far as the beta goes, is sort of off the charts in terms of interest, which is fantastic. And as you mentioned, we do see server and increasingly more of a data center customers, it being a factor in their movement, right?
It being a factor in their migration. There’s a clear logical understanding among customers that the large language model driven and machine learning driven features are based in the cloud, which means that the customers move to the cloud in order to get access to those features. And it is another reason in a whole tapestry of reasons why customers are looking to move and we’ve certainly seen really great adoption of those features so far. Really excited about Atlassian Intelligence. Really excited about virtual agents in Jira Service Management, continuing to just drive straight efficiencies for customers and again driving that movement up to premium enterprise editions as we’ve talked about beforehand. And lastly, as I mentioned earlier, Loom AI and the Loom intelligence features that we shipped last month, again, driving great adoption of Loom because it’s a different category than the other Atlassian Intelligence features, but the ability to create and consume video more efficiently is really quite fantastic using some of these technologies.
So I don’t think our excitement could be higher and our commitment and the amount of resources we’re spending in R&D to do this equal to the best in the world is paramount for us.
Operator: Your next question comes from Ari Terjanian from Cleveland Research. Please go ahead.
Ari Terjanian: Hello. Thank you for taking the question. Strength in deferred revenue performance was notable. I was wondering if you could help unpack how much some of the newer initiatives around step-up credits, dual licensing, hybrid ELAs, as well as Atlassian Advisory Services help drive the strength in the larger enterprise deals there. And how should we think about some of those newer programs flowing through to revenue over the coming quarters, meaning to the extent there was dual licensing, how does that flow through to DC and cloud? And similarly, advisory services, how does that flow through to revenue, be it showing up in other or cloud or DC? Thank you.
Joe Binz: Yeah. Thanks, Ari. This is Joe. You’re right. We were thrilled with our billings performance in the quarter. It was higher than we expected and was a record for the company. As you mentioned, you see this performance in our [indiscernible] revenue balance, which accelerated to 30% year-over-year growth. You’ll also see it in the remaining performance obligations, which increased over $1.9 billion. The outperformance there this quarter was driven by great sales execution that we talked about earlier and that resulted in several large multi-year agreements. And those are the agreements that you were referencing, hybrid ELAs, dual licensing, they’re having a material impact on our ability to grow our business in the enterprise space.
I’d say the way you’re going to see that show up is primarily in the form of migrations because a lot of that is targeted at establishing those relationships with our customers over multiple years. Many of those customers are using data centers as a stepping stone until they’re ready to move to the cloud. It shows up both in a data center and in our cloud revenue. It grows from a P&L accounting perspective. And we basically attribute revenue based on the relative list price between those two. So it’s roughly 50-50, give or take, between those two things as you think about the mechanical accounting of it.
Operator: Thank you. That’s all the questions we have time for today. I will now turn the call over to Mike for closing remarks.
Mike Cannon-Brookes: Thanks everyone for joining the call today from wherever you join in the world. We really really appreciate you being here. As always also appreciate your questions and continued support of Atlassian and analysis. A small note, we look forward to seeing all of you hopefully at Team 24 in Las Vegas at the end of April. And with that, have a kick-ass weekend.
